1. Technical Field
Aspects of the present invention relate to antennas. More particularly, aspects of the present invention relate to modifying beams from antennas to maximize throughput through a network while maintaining quality of service requirements.
2. Related Art
Mobile operators and suppliers constantly search for ways to respond to the increasing demand for ubiquitous mobile services. Mobile operators adjust a network's architecture so that they can introduce new higher speed technologies quickly, while suppliers are working to devise ways for improving the capacity of their wireless products. Current trends indicate:                a. Mobile operators have embarked on using wireless local area network (WLAN) technologies to cover hotspots (e.g., airports, shopping malls, etc.) within their cellular networks, and WLANs are already the prevalent means of providing mobile services within large enterprises.        b. Wireless suppliers are exploring adaptive array antenna (dubbed as either “smart” or adaptive antenna) technology as a promising technique for increasing the capacity of their cellular and WLAN products. A “smart” antenna may include an array of radiating antenna elements where the smart antenna radiation patterns, i.e., the smart antenna beams, as well as the directions of these beams may be altered by adjusting relevant parameters (e.g., amplitude and relative phase) on different array elements. Since each beam of a smart antenna has a distinct carrier frequency, and represents a distinct physical channel, the terms “beam” and “frequency channel” are used herein interchangablely.        
The current approaches are cumbersome. They do not dynamically adapt directions of frequency channels relevant to at least one of locations and traffic characteristics.
Conventional analytical beam forming techniques usually adjust/control the relevant parameters of a smart antenna such that the signal to noise and interference ratio (SNIR) of each frequency channel is minimized, and its capacity is maximized. The prevalent “optimality” criteria for beam forming techniques are the minimum mean square error (MMSE), and least square (LS) techniques. These techniques use optimal filtering theory to devise a recursive spatial filter that minimizes the square of the difference between the antenna array output and locally generated estimate of the desired signals of subscribers (i.e., a local reference signal) at the transceiver. The MMSE and LS techniques require that the transceiver have either a-priori knowledge or an estimate of the desired signals of subscribers. These estimates are usually obtained using methods such as periodic training sequences, decision directed adaptation, etc. However, they do not dynamically address traffic concerns or locations.